The Use of Maximum Likelihood Estimation for Forming Images of Diffuse Radar Targets from Delay-Doppler Data

Donald L. Snyder; Joseph A. O'Sullivan; Michael I. Miller

doi:10.1109/18.30975

The Use of Maximum Likelihood Estimation for Forming Images of Diffuse Radar Targets from Delay-Doppler Data

Donald L. Snyder
, Joseph A. O'Sullivan
, Michael I. Miller

Research output: Contribution to journal › Article › peer-review

52 Scopus citations

Abstract

A new approach to high-resolution radar imaging is presented. The starting point is a model of the radar echo signal based on the physics governing radar reflections. This model has been used several times in the past for describing radar targets that are rough compared to the wavelength of the transmitted radiation. Without specifying precisely what the transmitted signal is, a general estimation-based procedure is derived for obtaining images. After discretizing the model, the radar imaging problem reduces to the task of estimating discretized second-order statistics of the reflectance process of the target. Maximum likelihood estimates of these statistics are obtained as the limit point of an expectation-maximization algorithm.

Original language	English
Pages (from-to)	536-548
Number of pages	13
Journal	IEEE Transactions on Information Theory
Volume	35
Issue number	3
DOIs	https://doi.org/10.1109/18.30975
State	Published - May 1989

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abstract = "A new approach to high-resolution radar imaging is presented. The starting point is a model of the radar echo signal based on the physics governing radar reflections. This model has been used several times in the past for describing radar targets that are rough compared to the wavelength of the transmitted radiation. Without specifying precisely what the transmitted signal is, a general estimation-based procedure is derived for obtaining images. After discretizing the model, the radar imaging problem reduces to the task of estimating discretized second-order statistics of the reflectance process of the target. Maximum likelihood estimates of these statistics are obtained as the limit point of an expectation-maximization algorithm.",

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N2 - A new approach to high-resolution radar imaging is presented. The starting point is a model of the radar echo signal based on the physics governing radar reflections. This model has been used several times in the past for describing radar targets that are rough compared to the wavelength of the transmitted radiation. Without specifying precisely what the transmitted signal is, a general estimation-based procedure is derived for obtaining images. After discretizing the model, the radar imaging problem reduces to the task of estimating discretized second-order statistics of the reflectance process of the target. Maximum likelihood estimates of these statistics are obtained as the limit point of an expectation-maximization algorithm.

AB - A new approach to high-resolution radar imaging is presented. The starting point is a model of the radar echo signal based on the physics governing radar reflections. This model has been used several times in the past for describing radar targets that are rough compared to the wavelength of the transmitted radiation. Without specifying precisely what the transmitted signal is, a general estimation-based procedure is derived for obtaining images. After discretizing the model, the radar imaging problem reduces to the task of estimating discretized second-order statistics of the reflectance process of the target. Maximum likelihood estimates of these statistics are obtained as the limit point of an expectation-maximization algorithm.

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JO - IEEE Transactions on Information Theory

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ER -

The Use of Maximum Likelihood Estimation for Forming Images of Diffuse Radar Targets from Delay-Doppler Data

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